Fitness consequences of social network position in a wild population of forked fungus beetles (Bolitotherus cornutus)

Abstract

Social networks describe the pattern of intraspecific interactions within a population. An individual’s position in a social network often is expected to influence its fitness, but only a few studies have examined this relationship in natural populations. We investigated the fitness consequences of network position in a wild beetle population. Copulation success of male beetles positively covaried with strength (a measure of network centrality) and negatively covaried with clustering coefficient (CC) (a measure of cliquishness). Further analysis using mediation path models suggested that the activity level of individuals drove the relationships between strength and fitness almost entirely. In contrast, selection on CC was not explained by individual behaviours. Although our data suggest that social network position can experience strong sexual selection, it is also clear that the relationships between fitness and some network metrics merely reflect variation in individual‐level behaviours.

The consequences of unidentifiable individuals for the analysis of an animal social network

“…By influencing behavioural traits, foraging success and disease status, social network position will often be fundamental in determining body condition, stress levels (Brent, Semple, Dubuc, Heistermann, & MacLarnon, 2011) and ultimately reproductive success (Formica et al, 2012;McDonald, 2007;Wey et al, 2013). In this regard, demonstrating the potential of using social network approaches in systems in which many individuals are not identifiable is highly important.…”

“…Social network analysis is now widely used to study animal social behaviour (Farine, Garroway, & Sheldon, 2012;PinterWollman et al, 2013;Sih, Hanser, & McHugh, 2009;Wey, Blumstein, Shen, & Jord an, 2008), and is fast developing beyond being a descriptive tool to become fundamental in quantifying behavioural interactions and their subsequent consequences in a wider social context (Dey, Reddon, O'Connor, & Balshine, 2013;Formica et al, 2012;Kohn, King, Dohme, Meredith, & West, 2013;Sueur, Jacobs, Amblard, Petit, & King, 2011;Wey, Burger, Ebensperger, & Hayes, 2013). There is a growing focus on understanding how an individual's personality, phenotype and condition interact to influence its social decision making and social strategy (Aplin et al, 2013;Croft et al, 2005Croft et al, , 2009Silk, Croft, Tregenza, & Bearhop, 2014;Wilson, Krause S., Dingemanse & Krause 2013).…”

“…There is a growing focus on understanding how an individual's personality, phenotype and condition interact to influence its social decision making and social strategy (Aplin et al, 2013;Croft et al, 2005Croft et al, , 2009Silk, Croft, Tregenza, & Bearhop, 2014;Wilson, Krause S., Dingemanse & Krause 2013). By studying variation in individual social position, it is possible to make inferences about both the mechanisms that drive population social structure in a study system (Connor, Heithaus, & Barre, 2001;Stanley & Dunbar, 2013;Wittemyer, Douglas-Hamilton, & Getz, 2005) and the consequences of following particular social strategies for individual fitness (Formica et al, 2012;McDonald, 2007;Wey et al, 2013). Extracting individual level metrics from networks is therefore a major application of social network analysis in behavioural ecology, and being able to apply network analysis to infer individual social behaviour in a wide range of systems becomes highly significant.…”

“…Additionally, there has been increasing recent interest in social network position as a personality trait or part of a wider behavioural syndrome (Krause, James, & Croft, 2010;Wilson, Krause, Dingemanse, & Krause, 2013). The role of these potential factors in influencing social position and the consequences to an individual of that social position can be investigated using a simple correlative approach at an individual level (Formica et al, 2012;Wey et al, 2013). This makes data from many marking or tagging projects highly valuable in generalizing our understanding of what processes drive individual social strategies and social evolution in many types of fissionefusion social system, and how this then contributes to variation in overall population social structure.…”

Agonistic reciprocity is associated with reduced male reproductive success within haremic social networks

“…Factor analysis revealed that only measures of male and alpha female network position were associated with new eggs (table 1 and figure 2a). Simple, dyadic interactions between the dominant male and female were not associated with new eggs, demonstrating that unlike factor 3 with HS, for which dyadic agonism was illuminating, social network analysis provided unique insight [24]. Although we could not quantify individual female RS, these data suggest alpha females contributed the most reproductively, as expected for her status and size [16,60].…”